The neural network bi-directionally communicating time series data hierarchically

Abstract

A method to handle general time series data is shown. At first time series data is divided into basic string where a component does not appear several times, and a neural network to accept the basic string is shown. Then, hierarchically connected neural network handles target time series data by considering a row of basic string to be time series data of the upper hierarchy. The movement of the neural network is described using the element similar element of the electronic circuit, but works on the principle that is different from the oscillation circuit resemblance systems using a shift register and the recurrent network. The movement is confirmed by simulation by the C language, and hierarchy constitution and bi-directionally communicateting are shown, too.